title: Clinical and molecular models of glioblastoma multiforme survival.
abstract: Glioblastoma multiforme (GBM), a highly aggressive form of brain cancer, results in a median survival of 12-15 months. For decades, researchers have explored the effects of clinical and molecular factors on this disease and have identified several candidate prognostic markers. In this study, we evaluated the use of multivariate classification models for differentiating between subsets of patients who survive a relatively long or short time. Data for this study came from The Cancer Genome Atlas (TCGA), a public repository containing clinical, treatment, histological and biomolecular variables for hundreds of patients. We applied variable-selection and classification algorithms in a cross-validated design and observed that predictive performance of the resulting models varied substantially across the algorithms and categories of data. The best-performing models were based on age, treatments and global DNA methylation. In this paper, we summarise our findings, discuss lessons learned in analysing TCGA data and offer recommendations for performing such analyses.
authors.affiliation: Department of Pharmacology and Toxicology, University of Utah, 201 Presidents Circle, Salt Lake City, 84112 UT, USA. stephen.piccolo@hsc.utah.edu
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Piccolo
authors.forename: Lewis J
authors.initials: LJ
authors.lastname: Frey
mesh_terms: D000465:Algorithms; D001932:Brain Neoplasms / Q000175:diagnosis / Q000235:genetics / Q000401:mortality*; D019175:DNA Methylation; D005909:Glioblastoma / Q000175:diagnosis / Q000235:genetics / Q000401:mortality*; D006801:Humans; D053208:Kaplan-Meier Estimate; D008958:Models, Molecular; D011379:Prognosis; D015996:Survival Rate